Aj Geddes Useful AI Prompts Kubernetes Deployment

Kubernetes Deployment

Table of Contents

• Overview
• When to Use
• Quick Start
• Reference Guides
• Best Practices

Overview

Master Kubernetes deployments for managing containerized applications at scale, including multi-container services, resource allocation, health checks, and rolling deployment strategies.

When to Use

• Container orchestration and management
• Multi-environment deployments (dev, staging, prod)
• Auto-scaling microservices
• Rolling updates and blue-green deployments
• Service discovery and load balancing
• Resource quota and limit management
• Pod networking and security policies

Quick Start

Minimal working example:

# kubernetes-deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: api-service
  namespace: production
  labels:
    app: api-service
    version: v1
spec:
  replicas: 3
  strategy:
    type: RollingUpdate
    rollingUpdate:
      maxSurge: 1
      maxUnavailable: 0
  selector:
    matchLabels:
      app: api-service
  template:
    metadata:
      labels:
        app: api-service
        version: v1
      annotations:
// ... (see reference guides for full implementation)

Reference Guides

Detailed implementations in the references/ directory:

Best Practices

✅ DO

• Use resource requests and limits
• Implement health checks (liveness, readiness)
• Use ConfigMaps for configuration
• Apply security context restrictions
• Use service accounts and RBAC
• Implement pod anti-affinity
• Use namespaces for isolation
• Enable pod security policies

❌ DON'T

• Use latest image tags in production
• Run containers as root
• Set unlimited resource usage
• Skip readiness probes
• Deploy without resource limits
• Mix configurations in container images
• Use default service accounts

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